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Providing patients with medical records access is one strategy that health systems can utilize to reduce medical errors. However, how often patients request corrections to their records on a national scale is unknown.

Predictive analytic models, including machine learning (ML) models, are increasingly integrated into electronic health record (EHR)-based decision support tools for clinicians. These models have the potential to improve care, but are challenging to internally validate, implement, and maintain over the long term. Principles of ML operations (MLOps) may inform development of infrastructure to support the entire ML lifecycle, from feature selection to long-term model deployment and retraining.

Sepsis is associated with high mortality, especially during the novel coronavirus disease 2019 (COVID-19) pandemic. Along with high monetary health care costs for sepsis treatment, there is a lasting impact on lives of sepsis survivors and their caregivers. Early identification is necessary to reduce the negative impact of sepsis and to improve patient outcomes. Prehospital data are among the earliest information collected by health care systems. Using these untapped sources [...]

The 21st Century Cures Act has accelerated adoption of OpenNotes, providing new opportunities for patient and family engagement in their care. However, these regulations present new challenges, particularly for pediatric health systems aiming to improve information sharing while minimizing risks associated with adolescent confidentiality and safety.

Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures).

This study aimed to develop a virtual electronic health record (EHR) training and optimization program and evaluate the impact of the virtual model on provider and staff burnout and electronic health record (EHR) experience.

Informed decision aids provide information in the context of the patient's values and improve informed decision making (IDM). To overcome barriers that interfere with IDM, our team developed an innovative iPad-based application (aka "app") to help patients make informed decisions about colorectal cancer screening. The app assesses patients' eligibility for screening, educates them about their options, and empowers them to request a test via the interactive decision aid.

One of the best practices for timely and efficient diagnoses of central nervous system (CNS) trauma and complex diseases is imaging. However, rates of imaging for CNS are high and impose a lot of costs to health care facilities in addition to exposing patients with negative impact of ionizing radiation.

Prostate cancer (PCa) is a severe public health issue and the most common cancer worldwide in men. Early diagnosis can lead to early treatment and long-term survival. The addition of the multiparametric magnetic resonance imaging in combination with ultrasound (mpMRI-U/S fusion) biopsy to the existing diagnostic tools improved prostate cancer detection. Use of both tools gradually increases in every day urological practice. Furthermore, advances in the area of information technology [...]

Costs vary substantially among electronic medical knowledge resources used for clinical decision support, warranting periodic assessment of institution-wide adoption.